Chat GPT and AI Applications as Islamic Religious Education Learning Assistants

We are glad to introduce you that the 2021 3rd International Conference on Artificial Intelligence Technologies and Applications (ICAITA 2021) was successfully held on September 10-12, 2021. In light of worldwide travel restriction and the impact of COVID-19, ICAITA 2021 was carried out in the form of virtual conference to avoid personnel gatherings. Because most participants were still highly enthusiastic about participating in this conference, we chose to carry out ICAITA 2021 via online platform according to the original schedule instead of postponing it.ICAITA 2021 is to bring together innovative academics and industrial experts in the field of Artificial Intelligence Technologies and Applications to a common forum. The primary goal of the conference is to promote research and developmental activities in Artificial Intelligence Technologies and Applications and another goal is to promote scientific information interchange between researchers, developers, engineers, students, and practitioners working all around the world. The conference will be held every year to make it an ideal platform for people to share views and experiences in Artificial Intelligence Technologies and Applications and related areas.This scientific event brings together more than 100 national and international researchers in artificial intelligence technologies and applications. During the conference, the conference model was divided into three sessions, including oral presentations, keynote speeches, and online Q&A discussion. In the first part, some scholars, whose submissions were selected as the excellent papers, were given about 5-10 minutes to perform their oral presentations one by one. Then in the second part, keynote speakers were each allocated 30-45 minutes to hold their speeches.We were pleased to invite three distinguished experts to present their insightful speeches. Our first keynote speaker, Prof. Yau Kok Lim, from Sunway University, Malaysia. His research interests include Applied artificial intelligence, 5G networks, Cognitiveradio networks, Routing and clustering, Trust and reputation, Intelligent transportation system. And then we had Prof. Peter Sincak, from Technical University of Kosice, Slovakia. His research includes Artificial Intelligence and Intelligent Systems. Lastly, we were glad to invite Chinthaka Premachandra, from Shibaura Institute of Technology, Sri Lanka. His research interests include Artificial Intelligence, image processing and robotics. In the last part of the conference, all participants were invited to join in a WeChat group to discuss and explore the academic issues after the presentations. The online discussion was lasted for about 30-60 minutes. The first two parts were conducted via online collaboration tool, Zoom, while the online discussion was carried out through instant communication tool, WeChat. The online platform enabled all participants to join this grand academic event from their own home.We are glad to share with you that we still received lots of submissions from the conference during this special period. Hence, we selected a bunch of high-quality papers and compiled them into the proceedings after rigorously reviewed them. These papers feature following topics but are not limited to: Artificial Intelligence Applications & Technologies, Computing and the Mind, Foundations of Artificial Intelligence and other related topics. All the papers have been through rigorous review and process to meet the requirements of international publication standard.Lastly, we would like to express our sincere gratitude to the Chairman, the distinguished keynote speakers, as well as all the participants. We also want to thank the publisher for publishing the proceedings. May the readers could enjoy the gain some valuable knowledge from the proceedings. We are expecting more and more experts and scholars from all over the world to join this international event next year.The Committee of ICAITA 2021List of titles Committee member, General Conference Chair, Technical Program Committee Chair, Academic Committee Chair, Technical Program Committee Member, Academic Committee Member are available in this Pdf.

This research aims to measure the influence of dependence on the use of artificial intelligence (AI) applications on the learning effectiveness of Islamic Education Management students. Using quantitative research methods, data was collected through questionnaires distributed to 150 students at several universities. Data analysis was carried out using a simple linear regression test to determine the correlation between the dependency variable on AI applications (X) and learning effectiveness (Y). The research results show that 78% of respondents use AI applications in their daily learning activities, with 65% of them feeling more efficient in accessing information. However, there are 40% of students who show decreased motivation for independent learning due to dependence on AI applications. The results of the regression test show that there is a significant positive correlation between the use of AI applications and learning effectiveness with a correlation coefficient of 0.52 and a significance of p < 0.05. These findings indicate that the use of AI plays an important role in increasing learning effectiveness, but also has the potential to reduce motivation for independent learning. It is hoped that the use of AI will be accompanied by learning strategies that support student independence and critical thinking.

PurposeThis study explored the different artificial intelligence (AI) applications used in academic libraries and the key factors and impediments related to their implementation.Design/methodology/approachThe author applied quantitative research methods in the form of a questionnaire, using both open and closed questions. A total of 472 valid questionnaires were received from academic librarians.FindingsThe author sought responses from librarians who had implemented AI applications and those who had not, identifying the types of AI applications implemented, key factors relating to their implementation, and impediments to promoting AI. Gaps were identified between the level of support for AI applications and the negative effect of the impediments. Furthermore, the more extensive the individual and organizational knowledge activities performed by the librarians and libraries held, the more positive the attitude was librarians' attitude toward AI applications in their libraries. However, librarians recognized that AI applications are inevitable, but indicated that the difficulties of in execution have hampered the adoption of AI.Research limitations/implicationsThe sample data were collected in Taiwan; therefore, the data may only represent the views of Taiwanese academic librarians on AI applications. The results of this study may not apply to librarians worldwide; however, they may provide a useful reference.Practical implicationsThe results revealed the top four AI applications that libraries would most likely implement in the near future. Therefore, AI application developers and suppliers can prioritize the promotion of these products for to academic libraries. This study revealed that funding and costs related to AI implementation were discovered to be key factors relating to implementing AI applications. Some impediments to the implementation of AI applications relate to technological problems. Several librarians suggested that managers should invest more resources at an early stage rather than reducing cutting back on human resources initially. Although worries regarding privacy and ethics were mentioned expressed by some respondents, most academic librarians did not regard these to be major concerns.Originality/valueThis study provides the perspectives of librarians who have implemented AI applications and of those who have not. In addition, it explores the advantages and disadvantages of AI applications, and the level of support for and impact of AI applications and promotions. This study also included a gap analysis. Moreover, individual and organizational knowledge activity scales were adopted to examine AI awareness and the perceptions of academic librarians.

This study examined artificial intelligence (AI) applications for health information service delivery throughout Africa and its subregions. The study aimed to review existing research, identify key AI applications in healthcare, assess their impact in African healthcare, and examine strategies that promote effective, ethical, and equitable integration for sustainable healthcare improvements across the continent. African healthcare systems face obstacles, including restricted access to quality information, shortages of healthcare professionals, and infrastructural limitations. AI presents promising solutions to these challenges. The article comprises a systematic literature review of peer-reviewed research on AI-driven health information service delivery in Africa between 2014 and 2024, examining key AI applications, opportunities, challenges, and ethical considerations associated with AI adoption in healthcare, and their influence on health information service delivery. This review examined African healthcare systems’ preparedness for AI adoption, the importance of digital literacy, and the infrastructure that affects AI dissemination. The study also examined ethical considerations, including data privacy, equity, and the risk of widening health disparities. The findings reveal that AI technologies can enhance the accessibility, precision, and efficiency of health information services across Africa, particularly in underserved areas. The primary obstacles to AI adoption include insufficient digital infrastructure, low digital literacy, and socio-cultural hurdles. This review emphasises addressing ethical concerns to ensure that AI-driven health information systems benefit all populations without exacerbating inequality. The review offers insights for policymakers, healthcare providers, and researchers. Areas for future research and development were reviewed to ensure sustainable and equitable AI integration across Africa’s healthcare systems. The study recommends that stakeholders invest in digital infrastructure, promote digital literacy, and establish ethical guidelines for successful and equitable AI integration into health information service delivery throughout Africa.

This study evaluates the impact of Artificial Intelligence (AI) applications in power systems on energy security and to determine relevant policy implications. We use a mixed methods approach to analyze the benefits and risks associated with AI implementation on the European power grid, focusing on four key dimensions of energy security: availability, affordability, accessibility, and acceptability. We investigated the benefits of AI using PyPSA, a Python-based model of the European electricity system. Three AI applications were parametrized: load reduction, load shifting, and wind wake steering. We compared scenarios in which these AI applications are widely deployed against a baseline scenario without these applications to determine if AI improves energy security. The study also analyzes risks associated with AI deployment in the power grid. We developed a risk taxonomy centered around six high-level categories: cybersecurity, jurisdictional or sovereignty issues, unexplained or unexpected actions by the model, unethical or illegal decision-making, reliance and trust in decision-making, and supplier dependency and vendor lock-in. Additionally, we conducted a back-casting exercise with subject-matter experts to determine positive and negative future outcomes of AI deployment and identify actions to create positive outcomes and avoid negative ones. The paper presents a set of policy implications for AI on the European synchronous grid. We find that AI applications can improve energy security in power systems. In the scenarios we tested, behind-the-meter applications have a greater impact on energy security than front-of-meter applications. The results suggest that AI applications targeting energy consumption may significantly improve energy security metrics. Keywords: Energy Security, AI, Power Grid, European Electricity System

Introduction: In todays rapidly changing technology, artificial intelligence (AI) is changing the way we live, work and create art at an unprecedented speed. As an important part of human culture, dance art has also ushered in new development opportunities and challenges in this scientific and technological revolution. Objectives: This paper aims to explore the innovative application and influence of artificial intelligence (AI) in dance creation and performance. With the rapid development of AI technology, its application is increasingly wide in the field of art, and dance art is no exception Methods: This paper first outlines the application of AI technology in dance creation, including the generation of new dance movements through algorithms, auxiliary choreography, etc. These applications provide unprecedented creative sources and tools for dance creators. Then, this paper analyzes the role of AI in dance performance, such as the accurate movement performance of dance robot, the immersive experience of virtual reality technology in dance performance, etc. Results: These technologies not only enrich the form of dance performance, but also broaden the viewing experience of the audience. In addition, this paper also discusses the application of AI in dance teaching, such as intelligent guidance system, distance dance teaching, etc., which bring convenience and personalization to dance teaching. However, the application of AI in the field of dance also faces technical challenges and art ethical issues, which need further research and discussion. Conclusions: In conclusion, this paper believes that the application of AI technology in dance creation, performance and teaching has broad prospects, but it also needs to pay attention to its potential impact and challenges to promote the harmonious coexistence of dance art and AI technology. The research of this paper provides new perspectives and thoughts in the field of dance art, Provides a reference for future research and practice.

Purpose This narrative review investigates the interplay between gender bias in artificial intelligence (AI) systems and the potential of digital literacy to empower women in technology. By synthesising research from 2010 to 2024, the study examines how gender bias manifests in AI, its impact on women’s participation in technology, and the effectiveness of digital literacy initiatives in addressing these disparities. Purpose A systematic literature search was conducted across major academic databases, including Web of Science, Scopus, IEEE Xplore, and Google Scholar. The review focused on peer-reviewed articles, reports, and case studies published between 2010 and 2024 that addressed gender bias in AI, women’s participation in technology, and digital literacy initiatives. A thematic analysis framework was employed to identify and synthesise recurring themes and patterns. Purpose The findings reveal systemic gender biases embedded in AI applications across diverse domains, such as recruitment, healthcare, and financial services. These biases stem from factors including the under-representation of women in AI development teams, biased training datasets, and algorithmic design choices. Digital literacy programs emerge as a promising intervention, fostering a critical awareness of AI bias, encouraging women to pursue AI careers, and catalysing growth in women-led AI projects. Purpose Although gender bias in AI poses significant challenges, this review highlights digital literacy as a transformative tool for achieving gender equity in AI development and application. The study highlights the importance of inclusive AI design, gender-responsive education policies, and sustained research efforts to mitigate bias and promote equity.

ObjectivesDifferent stakeholders may hold varying attitudes towards artificial intelligence (AI) applications in healthcare, which may constrain their acceptance if AI developers fail to take them into account. We set out...

With the rapid development of modern information electronic technology, artificial intelligence information technology has gradually penetrated into all fields of human society. This paper aims to improve the clinical assistant nurses’ correct understanding of medical artificial intelligence, and to provide an important reference for further promoting the wide application and development of clinical artificial machine intelligence in the field of clinical nursing in China. In this paper, through the comparison of intelligent nursing and traditional nursing effect monitoring, as well as the analysis of medical staff and patients’ satisfaction with artificial intelligence treatment time, treatment effect and treatment scheme, and the results were discussed and analyzed. The problems that should be paid attention to in the application of artificial intelligence in clinical nursing were put forward, which provided guarantee for the development of clinical nursing. The research in this paper has important practical significance for the further development of the two.KeywordsIn the information ageArtificial intelligenceClinical nursingSmart devices

BackgroundResearch on technologies based on artificial intelligence in healthcare has increased during the last decade, with applications showing great potential in assisting and improving care. However, introducing these technologies into nursing can raise concerns related to data bias in the context of training algorithms and potential implications for certain populations. Little evidence exists in the extant literature regarding the efficacious application of many artificial intelligence -based health technologies used in healthcare. ObjectivesTo synthesize currently available state-of the-art research in artificial intelligence -based technologies applied in nursing practice. DesignScoping review MethodsPubMed, CINAHL, Web of Science and IEEE Xplore were searched for relevant articles with queries that combine names and terms related to nursing, artificial intelligence and machine learning methods. Included studies focused on developing or validating artificial intelligence -based technologies with a clear description of their impacts on nursing. We excluded non-experimental studies and research targeted at robotics, nursing management and technologies used in nursing research and education. ResultsA total of 7610 articles published between January 2010 and March 2021 were revealed, with 93 articles included in this review. Most studies explored the technology development (n = 55, 59.1%) and formation (testing) (n = 28, 30.1%) phases, followed by implementation (n = 9, 9.7%) and operational (n = 1, 1.1%) phases. The vast majority (73.1%) of studies provided evidence with a descriptive design (level VI) while only a small portion (4.3%) were randomised controlled trials (level II). The study aims, settings and methods were poorly described in the articles, and discussion of ethical considerations were lacking in 36.6% of studies. Additionally, one-third of papers (33.3%) were reported without the involvement of nurses. ConclusionsContemporary research on applications of artificial intelligence -based technologies in nursing mainly cover the earlier stages of technology development, leaving scarce evidence of the impact of these technologies and implementation aspects into practice. The content of research reported is varied. Therefore, guidelines on research reporting and implementing artificial intelligence -based technologies in nursing are needed. Furthermore, integrating basic knowledge of artificial intelligence -related technologies and their applications in nursing education is imperative, and interventions to increase the inclusion of nurses throughout the technology research and development process is needed.

Background and aimMedical students are expected to be familiar with artificial intelligence (AI) applications in healthcare. This cross-sectional study looked at the attitudes, thoughts, and understanding of healthcare students toward AI.Materials and methodsDuring the academic year 2023-2024, medical students enrolled in the College of Medicine and Health Sciences (CMHS) at the Arabian Gulf University (AGU) were included in this study. A questionnaire was developed to evaluate their understanding and opinions regarding the use of AI in medical training. These data were gathered, categorized, and analyzed using the Statistical Package for Social Sciences (SPSS) version 29 (IBM Corp., Armonk, NY, US). Categorical variables were shown in the form of frequencies and percentages, whereas continuous variables were presented as mean and standard deviation (SD). Chi-square tests were utilized for comparing categorical variables. A p-value of <0.05 was considered statistically significant.ResultsThe study found that n=41 (27%) of medical students are very familiar with AI applications while n=92 (60.5%) are somewhat familiar. Familiarity increases as students progress in their medical education, with senior clinical phase students more familiar than juniors. There was no significant difference in perceptions of AI application among medical phases. Familiarity with research methodology and studies increases familiarity with AI applications. Most students believe AI will have a positive impact on medical education, but perceptions vary by educational phase. Many students support integrating AI into curricula with 67 (44.1%) of students using AI applications, with a higher percentage in pre-clinical phases, likely due to application in research projects in this phase. Concerns were raised about AI impacting the human touch in medical practice and doctor-patient communication, as well as technical challenges faced by students when applying AI.ConclusionArab Gulf medical students show positive attitudes toward AI applications in medical education. Tailored educational strategies are needed to optimize AI integration in medical practice and address concerns effectively.

Artificial intelligence (AI) applications for clinical genetics hold the potential to improve patient care through supporting diagnostics and management as well as automating administrative tasks, thus enhancing and potentially enabling clinician/patient interactions. While the introduction of AI into clinical genetics is increasing, there remain unclear questions about risks and benefits, and the readiness of the workforce. To assess the current clinical genetics workforce's use, knowledge, and attitudes toward available medical AI applications, we conducted a survey involving 215 US-based genetics clinicians and trainees. Over half (51.2%) of participants report little to no knowledge of AI in clinical genetics and 64.3% reported no formal training in AI applications. Formal training directly correlated with self-reported knowledge of AI in clinical genetics, with 69.3% of respondents with formal training reporting intermediate to extensive knowledge of AI vs. 37.5% without formal training. Most participants reported that they lacked sufficient knowledge of clinical AI (83.4%) and agreed that there should be more education in this area (97.6%) and would take a course if offered (89.3%). The majority (51.6%) of clinician participants said they never used AI applications in the clinic. However, after a tutorial describing clinical AI applications, 75.8% reported some use of AI applications in the clinic. When asked specifically about clinical AI application usage, the majority of clinician participants used facial diagnostic applications (54.9%) and AI-generated genomic testing results (62.1%), whereas other applications such as chatbots, large language models (LLMs), pedigree or medical summary generators, and risk assessment were only used by a fraction of the clinicians, ranging from 11.1 to 12.5%. Nearly all participants (94.6%) reported clinical genetics professionals as being overburdened. Further clinician education is both desired and needed to optimally utilize clinical AI applications with the potential to enhance patient care and alleviate the current strain on genetics clinics.

Artificial intelligence (AI) applications in healthcare and considerations for nursing education

Technological progress, especially in the field of information, has led to reducing the gap between science, information and knowledge. This accelerating change has forced all educational institutions to comply with this new mission by using information technology in the teaching process, as artificial intelligence has become an integral part of the educational and learning process, and a means of Effective in the teaching process, in addition to being research tools in obtaining information and knowledge, the research problem focused on (what are the attitudes of the kindergarten teacher towards using artificial intelligence applications in the effective teaching process in the early education stage in the third Rusafa Education Directorate?), where the importance of The research is considered one of the researches that deals with an important and vital topic (artificial intelligence), as it gains its importance in that it represents the role that kindergarten teachers play in the early education stage in developing the skills and abilities and refining the information of the child through their use of artificial intelligence methods and applications, as well as The positive role of such research in stimulating kindergarten teachers’ motivation to benefit from artificial intelligence applications, which increases the efficiency and effectiveness of their teaching. The aim of the research is to reveal kindergarten teachers’ attitudes towards using artificial intelligence in the effective teaching process in the early education stage, as well as to reveal the most important The challenges facing kindergarten teachers using artificial intelligence in the effective teaching process, and are there any statistically significant differences between the average kindergarten teacher’s attitudes to using artificial intelligence in the effective teaching process in the early education stage according to the research variables? The research reached several conclusions, perhaps the most important of which is the existence of differences. There is statistical significance between the average kindergarten teacher’s attitudes to using artificial intelligence in the effective teaching process in the early education stage according to the research variables. The research recommends holding many workshops and training courses for kindergarten teachers on how to use artificial intelligence in effective teaching, and including programs and rehabilitation plans for kindergarten teachers. About the use of artificial intelligence according to the plans of the Ministry of Education, which are consistent with its vision, and encouraging teachers to proceed and benefit from applications and websites for safe and available artificial intelligence applications in the teaching process

In the time we live in, the digital competencies of employees represent an important factor in achieving positive business results. In this sense, the integration and application of modern technologies and artificial intelligence in the learning and teaching process is of crucial importance in the information society of the 21st century. It is precisely the emergence of artificial intelligence and the rapid development of ICT that constantly affects the challenges of life and work, and therefore the success of students through the education system as members of a society in which ICT is an indispensable part. It is known that the development of information technologies has initiated improvement in various areas such as: finance, business, health, education, and the entire labour market. In this research work, it will be evolved to a new review of the relevant literature and research in practice, how artificial intelligence can influence the outcome of the educational process and increase the entrepreneurial competencies of employees. In this direction, this research will present a research study of questionnaires applied for analysis and obtaining data on training and testing for statistical evaluation. Statistical analysis will be based on the application of artificial intelligence, i.e., Adaptive Neuro-Fuzzy Inference Systems (ANFIS). In this research, we use the ANFIS methodology to determine the most important factors of student success in teaching. Based on the review of the relevant literature, it is evident that there is not enough research that would deal with the analysis of the relationship between students' success in mathematics and the factors that influence it. This is confirmed by the research results, which indicate that the quality of students' work in practice is influenced by several different factors: educational technology, teacher competence, teacher motivation, etc. This type of research fills the gap in the lack of research to determine which key factors have the strongest impact on student success. The research results of this paper confirm that the application of artificial intelligence in teaching through educational software, among other things, can be a key success factor for improving teaching. In this sense, the effects of the application of artificial intelligence and specific educational software and the effects they have on student motivation, that is, the interest and self-confidence of all factors of the educational process, have been identified. The obtained results indicate the benefits and advantages that educational institutions can have from the introduction of educational technologies in teaching. In this way, technology has become not only useful, but also a necessary instrument for purposeful action in society. The results of the research show that artificial intelligence through Neuro-fuzzy architecture was created with the aim of overcoming complex and complex problems, it has its application in situations that are mostly impossible to describe analytically. Once learned ways to overcome complex problems, they can be applied after schooling in order to contribute to raising the entrepreneurial competencies of pupils and students, which will lead to the improvement and modernization of business and help you stay relevant in the labour market.